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Thanks to Toby now the program takes:

--- 7.169409990310669 seconds to finish the program--- instead of --- 186.7168517112732 seconds--- for 100 milion numbers.

One other improvement I made was to add an extra optimization on the random generating algorithm, using numpy. So numpy.sort() was used to sort the numpy array, because it is faster for numpy arrays.

Code

import time
import numpy

start_time0 = time.time()


def median(values):
    sortedlist =  numpy.sort(values)
    length = len(sortedlist)
    half = length // 2

    if length % 2 == 0:
        return (sortedlist[half] + sortedlist[half - 1]) // 2
    else:
        return sortedlist[half]


def main():

    m, n = 1000, 100000000
    # Random Number Generator
    start_time = time.time()
    data = numpy.random.randint(1, m, n)
    print("--- %s seconds to numpy random---" % (time.time() - start_time))
    # Median
    start_time = time.time()
    result = median(data)
    print("Result: ", result)
    print("--- %s seconds to find the Median---" % (time.time() - start_time))


if __name__ == "__main__":

    main()
    print("--- %s seconds to finish the program---" % (time.time() - start_time0))